Video object tracking is the process of locating a moving object or multiple objects over time using one or multiple cameras. It has a variety of uses, some of which are: human-computer interaction, security and surveillance, video communication and compression, augmented reality, traffic control, medical imaging and video editing. Video object tracking can be a time consuming process due to the amount of data that is contained in video. Adding further to the complexity is the possible need to use object recognition techniques for tracking, a challenging problem in its own right.
The objective of video object tracking is to detect and then associate a target object's image projections in consecutive video frames as it changes its position. The association may be difficult when the object is moving fast relative to the frame rate or when multiple objects are being tracked. Another situation that increases the complexity of the problem is when the tracked object changes its orientation and pose over time. To address this complexity, video object tracking systems usually employ an object model which characterizes the object's appearance and motion.
Automated video object tracking applications are known in the art. Generally, such applications receive video frames as input, and act to detect objects of interest within the frame images, such as moving objects or the like, frequently using background subtraction techniques. Having detected an object within a single input frame, such applications further act to track the detected object from frame to frame, using characteristic features of the detected object. For example, establishing a track may be accomplished by detecting objects in a received input frame, determining the characteristic features of these detected objects, and, then, associating these detected objects with corresponding objects, detected in previously received input frames, based on matching characteristic features.